Data Quality Expert, Giza Arabia, Riyadh, KSA

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Job Description

 
Job Description:

    Develop and lead the implementation of enterprise-level data quality standards, policies, and procedures.
    Oversee data quality assessments, audits, and profiling to identify issues, root causes, and improvement opportunities.
    Collaborate with data stewards, data architects, and business stakeholders to establish data quality metrics and KPIs.
    Design and implement robust data cleansing, enrichment, and validation strategies across diverse data sources and platforms.
    Monitor and report on data quality performance, ensuring transparency and accountability throughout the organization.
    Evaluate and integrate data quality tools, technologies, and automation solutions to enhance efficiency and accuracy.
    Provide expert guidance and training to teams on data quality best practices, methodologies, and regulatory compliance.
    Lead cross-functional initiatives to address complex data quality challenges and drive continuous improvement.
    Ensure alignment of data quality efforts with overall data governance and business objectives.
    Stay current with industry trends, emerging technologies, and evolving regulatory requirements to maintain excellence in data quality practices.

Personal Skills

 

    Data Quality Frameworks and Standards:
    Deep understanding of frameworks for data quality assessment, monitoring, and improvement.
    Data Profiling and Assessment Tools:
    Proficiency with data profiling, auditing, and lineage tracking tools (e.g., Collibra, Informatica Data Quality).
    Root Cause Analysis:
    Ability to identify, analyze, and resolve underlying causes of data quality issues.
    Data Cleansing and Enrichment:
    Expertise in designing and implementing data cleansing, standardization, and enrichment processes.
    SQL and Scripting Languages:
    Strong command of SQL and possibly Python or R to query, analyze, and transform data.
    Data Governance and Compliance:
    Familiarity with governance frameworks, regulatory standards (e.g., GDPR, CCPA), and compliance best practices.
    ETL/ELT Processes:
    Experience with ETL/ELT tools and techniques to integrate and maintain data quality in data pipelines.
    Performance Measurement:
    Skill in defining and tracking data quality metrics, KPIs, and performance dashboards.
    Communication and Collaboration:
    Excellent communication and interpersonal skills to work effectively with stakeholders, data stewards, and technical teams.
    Continuous Improvement Mindset:
    Commitment to staying updated with industry trends, best practices, and emerging technologies to continually enhance data quality initiatives.

 Technical Skills

Data Quality Tools: Proficiency with industry-standard data quality and profiling tools (e.g., Informatica Data Quality, Talend Data Quality, Collibra).SQL and Database Querying: Advanced SQL skills to query databases, identify anomalies, and perform complex data transformations.


Scripting and Programming: Familiarity with scripting languages (e.g., Python, R) for data cleansing, enrichment, and automation tasks.


ETL/ELT Tools: Experience with ETL/ELT platforms (e.g., Informatica, Talend, AWS Glue) to implement data quality rules and workflows.

Metadata Management: Ability to leverage metadata repositories and data catalogs to maintain data lineage and track data quality improvements.


Big Data and Cloud Platforms: Knowledge of big data ecosystems (Hadoop, Spark) and cloud environments (AWS, Azure, GCP) for scalable data quality solutions.

Data Governance Technologies: Familiarity with governance platforms and frameworks to ensure alignment of data quality initiatives with organizational standards.


Version Control and CI/CD: Experience using Git, Jenkins, or similar tools to manage code, automate deployments, and streamline data quality integrations.


Data Visualization: Skill in creating dashboards and visualizations (e.g., Tableau, Power BI) to communicate data quality metrics and trends.


APIs and Integration Technologies: Ability to use APIs, RESTful services, or messaging systems (e.g., Kafka) for seamless data integration and quality checks.

DETAILS TO REGISTER FOR THIS JOB:
NOTE: ATS-friendly CV is COMPULSORY!

https://www.gizasystemscareers.com/en/saudi-arabia/jobs/data-quality-expert-5224487/


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